In addition to providing printed telephone directories, telephone companies provide telephone directory assistance services. Users of these services call predetermined telephone numbers and are connected to directory assistance operators. The operators access directory databases to locate the directory listings requested by the users, and release the telephone numbers of those listings to the users.
Because telephone companies handle a very large number of directory assistance calls per year, the associated labor costs are very significant. Consequently, telephone companies and telephone equipment manufacturers have devoted considerable effort to the development of systems which reduce the labor costs associated with providing directory assistance services.
One difficulty associated with the automation of directory assistance services is the requirement to process in real time databases including a very large number of orthographies. In essence, two factors limit the real-time performance of a speech recognition system, namely memory and processor throughput. Due to increased memory capabilities in the speech recognition hardware, the memory constraints is never reached. In rare cases, where indeed the memory capacity is exhausted, it is possible to increase that capacity at a relatively low cost. Therefore, the real limiting factor in a real-time speech recognition system is processor throughput. Given the maximum processor throughput achievable, it is possible to compute the maximum sized vocabulary that can be processed. Presently, a typical machine can process a recognition acoustic graph consisting of 130,000 nodes.
The benefit of a speech recognition vocabulary is usually measured in terms of savings in operator working time. Indeed, if a single orthography in the vocabulary can save a few seconds of operator's time daily, this entry is highly desirable in the vocabulary since it yields net productivity gain. Take the example of a restaurant listing "The Red Ship" in a given locality. If this listing is requested often by callers, its inclusion in the vocabulary is highly desirable because it frees operator's time as the recognition process and release of the telephone number to the caller is effected without any human intervention. On the other hand, the vocabulary also contains orthographies which are confusing and often lead to low recognition probabilities. Those entries in the vocabulary are not very beneficial since they lead to situations that must be resolved with the assistance of the human operator. Thus, the processing time invested in attempting to automatically process the request is wasted since ultimately the operator has to be involved.
Against this background it becomes apparent that there is a need in the industry to develop a method and an apparatus that is capable of effecting a vocabulary selection to derive a sub-set of a large speech recognition dictionary that improves the process of directory assistance.